11 papers
Learning What to Remember and What to Internalize in LLM Self-Evolution via Adaptive Memory-Parameter Coordination
Tianyun Ji, Zhenya Huang, Jiayu Liu +3
Large language model agents increasingly operate in dynamic environments where tool interfaces, APIs, and user requirements change after deployment. Existing self-evolution methods…
PaperScout: An Autonomous Agent for Academic Paper Search with Process-Aware Sequence-Level Policy Optimization
Tingyue Pan, Jie Ouyang, Mingyue Cheng +6
Academic paper search is a fundamental task in scientific research, yet most existing approaches rely on rigid, predefined workflows that struggle with complex, conditional queries…
Survey of Computerized Adaptive Testing: A Machine Learning Perspective
Yan Zhuang, Qi Liu, Haoyang Bi +12
Computerized Adaptive Testing (CAT) offers an efficient and personalized method for assessing examinee proficiency by dynamically adjusting test questions based on individual perfo…
StaTS: Spectral Trajectory Schedule Learning for Adaptive Time Series Forecasting with Frequency Guided Denoiser
Jintao Zhang, Zirui Liu, Mingyue Cheng +3
Diffusion models have been used for probabilistic time series forecasting and show strong potential. However, fixed noise schedules often produce intermediate states that are hard…
PaperArena: An Evaluation Benchmark for Tool-Augmented Agentic Reasoning on Scientific Literature
Daoyu Wang, Mingyue Cheng, Shuo Yu +4
Understanding and reasoning on the large-scale scientific literature is a crucial touchstone for large language model (LLM) based agents. However, existing works are mainly restric…
Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts?
Qingchuan Li, Jiatong Li, Zirui Liu +4
Logical reasoning with large language models (LLMs) has received growing attention. One mainstream approach translates natural language into formal logic and then applies symbolic…